This research investigates the bio-products/phase change material (PCM) composites for the building envelope application. Bio-products, such as wood and herb, are porous medium, which can be applied in the building envelope for thermal insulation purpose. PCM is infiltrated into the bio-product (porous medium) to form a composite material. The PCM can absorb/release large amount of latent heat of fusion from/to the building environment during the melting/solidification process. Hence, the PCM-based composite material in the building envelope can efficiently adjust the building interior temperature by utilizing the phase change process, which improves the thermal insulation, and therefore, reduces the load on the HVAC system. Paraffin wax was considered as the PCM in the current studies. The building energy savings were investigated by comparing the composite building envelope material with the conventional material in a unique Zero-Energy (ZØE) Research Lab building at University of North Texas (UNT) through building energy simulation programs (i.e., eQUEST and EnergyPlus). The exact climatic conditions of the local area (Denton, Texas) were used as the input values in the simulations. It was found that the EnergyPlus building simulation program was more suitable for the PCM based building envelope using the latent heat property. Therefore, based on the EnergyPlus simulations, when the conventional structure insulated panel (SIP) in the roof and wall structures were replaced by the herb panel or herb/PCM composite, it was found that around 16.0% of energy savings in heating load and 11.0% in cooling load were obtained by using PCM in the bio-product porous medium.

Le travail de thèse présenté dans ce manuscrit traite du développement de dispositifs à base de dioxyde de vanadium VO₂ et de méta-surfaces dans le moyen infrarouge pour des applications passives et une intégration sur des lasers à cascade quantique (QCL). Ce travail a permis l'élaboration de nouvelles conditions de dépôt du matériau à changement de phase VO₂ par ablation laser pulsé à des températures compatibles avec les hétérostructures de III-V utilisées en optoélectronique. Les caractérisations des couches minces déposées montrent un changement de la réflectivité et de la conductivité électrique entre l'état isolant à basse température et l'état métallique à haute température autour de 68°C (341 K). Des développements ont ensuite été menés sur l'emploi d'un réseau de méta-surfaces permettant d'obtenir une couche homogène d'indice de réfraction effectif résonnant. Ces méta-surfaces sont constituées de résonateurs à anneau fendu dont la fréquence de résonance peut être ajustée par le choix de leurs paramètres géométriques et des matériaux les constituant. Une modulation optique de plus de 100cm-1 du pic de la résonance a été obtenue lors de la transition de phase avec des méta-surfaces déposées sur un film de VO₂. Ce résultat est très prometteur pour la conception de dispositifs monolithiques, robustes, compacts, accordables en fréquence et dont les propriétés optiques ne dépendent que de la température de la couche de VO₂.Enfin, ce travail étudie la fonctionnalisation des QCL dans le moyen infrarouge (7-8 µm) par des couches de VO₂ et de méta-surfaces. Il vise à comprendre l’influence des couches intégrées sur les propriétés d’émission. Afin de garantir une bonne interaction entre ces couches et le mode guidé du laser tout en ayant des pertes optiques faibles, des nouveaux guides d'onde ont été modélisés, puis les premiers QCL à base de VO₂ ont été démontrés et une température maximale de fonctionnement de 334 K a été mesurée. / The thesis work presented in this manuscript deals with the development of vanadium dioxide VO₂ and meta-surfaces based devices in the mid-infrared for passive applications and an integration on quantum cascade lasers (QCL).This work enabled the elaboration of new deposition conditions for the VO₂ phase change material by pulsed laser ablation at temperatures compatible with III-V heterostructures used in optoelectronics. The characterizations of the VO₂ coated thin films show a change in reflectivity and in electric conductivity between the insulating state at low temperature and the metallic state at high temperature around 68°C (341 K).Developments were then carried out on the use of a meta-surfaces array in order to obtain an homogeneous layer of resonant effective refractive index. These meta-surfaces are constituted by split-ring resonators, whose resonance frequency can be adjusted by choosing their geometric parameters and the materials they are made of. An optical modulation of more than 100cm-1 of the resonance peak has been obtained during the phase transition with meta-surfaces deposited on a VO₂ layer. This result is very promising for the conception of monolithic, robust, compact, frequency tunable devices and whose optical properties only depend on the VO₂ layer temperature.Finally, this work studies the functionalization of mid-infrared QCL (7-8 µm) with VO₂ and meta-surfaces layers. It aims at understanding the influence of the integrated layers on the emission properties. In order to ensure a good interaction between these layers and the laser guided mode while having low optical losses, new waveguides were modeled, then the first VO₂ based QCL have been demonstrated and a maximum operating temperature of 334 K has been measured.

No description available.

Funktionskläder utgör idag en stor marknad över hela världen med stigande efterfrågan där syntetiska material står för en betydande andel av de producerade textilierna. Ett plaggs totala miljöpåverkan kan till stor del härledas till materialvalet. Materialkompositionen i underställ består ofta av blandningar av textila fibrer, vilket komplicerar återvinningsprocessen och gör den nästintill omöjlig. För att kunna 'sluta cirkeln' måste innovativa textila lösningar tas fram för att styra textilindustrin i rätt riktning. Studien undersöker alternativa fibrer och jämför dem med de konventionella för textilier till underställ där man vill uppnå god fukttransport och värmeisolering. Vidare kartläggs materialens användningsområden för att skapa ett mångsidigt funktionsplagg och därmed möjliggöra en klimatsmartare garderob. Studien identifierar och jämför de termofysiologiska egenskaperna hos materialen bambuviskos, merinoull, Tencel, PCM och Coolmax. Textilprover stickades i hundraprocentiga materialkompositioner med en utvald trikåbindning i en rundsticksmaskin. Textilprovets termofysiologiska egenskaper utvärderades med hjälp av testutrustningarna Hudmodellen och WickView för att bestämma värmemotstånd och fukttransport. Därefter analyserades resultaten på materialens termofysiologiska komfort för att sedan kartlägga deras användningsområde baserat på aktivitetsnivå och omgivningsfaktorer. Resultaten från studien indikerar att merinoull och Coolmax kan rekommenderas för användning i underställ där både värmeisolering och fukttransport är viktiga, där merinoull är mest lämplig för kalla klimat. Vidare kan bambuviskos och Tencel vara lämpliga alternativ för användning i underställ vid aktiviteter av måttlig intensitet i varierande klimatförhållanden. PCM, med sitt låga värmemotstånd och medelhöga fukttransport, gör materialet mindre lämpligt för underställ. Testresultaten från studien ger insikt i materialens termofysiologiska komfort, men bör inte ses som en heltäckande bild av denna komfort. För att erhålla en mer valid slutsats krävs ytterligare tester och beaktande av fler faktorer. / Functional clothing represents a significant global market with rising demand today, where synthetic materials account for a considerable proportion of the textiles produced. A garment's total environmental impact can largely be traced back to the choice of material. The material composition of base layers often consists of mixtures of textile fibers, which complicates the recycling process and makes it almost impossible. To 'close the loop', innovative textile solutions must be developed to steer the textile industry in the right direction. The study investigates alternative fibers and compares them with conventional ones for textiles in base layers where effective moisture transport and heat insulation are sought. Furthermore, the areas of use for these materials are mapped out to create a versatile functional garment, thereby enabling a more climate-smart wardrobe. The study identifies and compares the thermophysiological properties of the materials bamboo viscose, merino wool, Tencel, PCM, and Coolmax. Textile samples were knitted in 100% material compositions using a selected tricot stitch on a circular knitting machine. The thermophysiological properties of the textile samples were evaluated using the Skin Model and WickView testing equipment to determine heat resistance and moisture transport. Afterwards, the results on the materials' thermophysiological comfort were analyzed, and their areas of use were mapped out based on activity level and environmental factors. The results from the study indicate that merino wool and Coolmax can be recommended for use in base layers where both heat insulation and moisture transport are important, with merino wool being most suitable for cold climates. Furthermore, bamboo viscose and Tencel could be suitable alternatives for use in base layers for activities of moderate intensity in varying climate conditions. PCM, with its low heat resistance and medium-high moisture transport, makes the material less suitable for base layers. The test results from the study provide insight into the materials' thermophysiological comfort but should not be seen as a comprehensive picture of this comfort. To obtain a more valid conclusion, additional tests and consideration of more factors are required.

Utilizing Phase Change Materials (PCM) for Latent Thermal Energy Storage (LTES) applications have previously been extensively researched as a measure to reduce greenhouse gas emissions from energy consumption. In order to make use of the waste heat from industrial processes for LTES purposes, a new demand emerged for PCMs capable of phase change in mid-temperature ranges of 100 °C - 200 °C. This higher temperature requirement made most of the previously studied material inapplicable as they had much lower melting and solidification temperatures. With this in mind, a new generation of PCMs consisting of Sugar Alcohols (SA) has been proposed. Erythritol is seen as an especially promising SA with good thermophysical properties for LTES purposes. However, it has been shown to suffer from severe supercooling, which makes it unreliable in real applications. To eradicate this issue, two additives, Graphene Oxide (GO) and Polyvinylpyrrolidone (PVP) at varying mass fractions were mixed with pure erythritol to form a composite which was studied using the Temperature-history (T-history) method to determine its effectiveness in reducing supercooling. Results show that at its most effective mass fraction, GO reduces supercooling by 28 o C and a 31 o C reduction is seen by the addition of PVP. The impacts on the duration of crystallization was also documented and analyzed using the same method. It was observed that the duration of crystallization was increased with increasing mass fractions of the additives. Other important properties of the composites were also studied in order to determine the overall feasibility for industrial applications. It includes analysis of the storage capacity through latent heat, changes in viscosity along with impacts on thermal diffusivity of the composites. / Att använda fasändringsmaterial (PCM) för termisk energilagring i form av latent värme (LTES) har tidigare extensivt forskats och undersökts som en lösning för att minska utsläppen av växthusgaser från energiförbrukning. För att utnyttja spillvärme från industriella processer för LTES-ändamål uppstod en efterfrågan på PCM som ändrar fas i temperaturer mellan 100 °C - 200 °C. Detta krav på högre temperatur gjorde att de flesta av de tidigare aktuella materialen inte kunde tillämpas eftersom de hade mycket lägre smält- och kristalliseringstemperaturer. Med detta i åtanke har en ny generation av PCM bestående av sockeralkoholer (SA) föreslagits. Erytritol ses som ett särskilt lovande SA med goda egenskaper för LTES-ändamål. Den har dock visat sig drabbas av svår underkylning, vilket gör den opålitligt i verkliga tillämpningar. För att utrota detta problem blandades två tillsatser, Graphene Oxide (GO) och Polyvinylpyrrolidone (PVP) vid olika massfraktioner med ren erytritol för att bilda en komposit som studerades med metoden Temperature-history (T-history) för att bestämma dess effektivitet på att minska underkylningen. Resultaten visar att GO på sin mest effektiva massfraktion minskar underkylningen med 28 o C och tillsats av PVP lyckats minska den med som mest 31 o C. Påverkningarna på varaktighet av kristallisering dokumenterades och analyserades med samma metod. Det var observerad att varaktigheten av kristallisering ökades med ökande massfraktioner av tillsatserna. Även andra viktiga egenskaper hos kompositerna studerades för att avgöra rimligheten att använda dessa för industriella tillämpningar. Det inkluderar analys av lagringskapaciteten genom latent värme, förändringar i viskositet tillsammans med påverkan på kompositernas termiska diffusivitet.

<div>The ‘Internet of Things’ has increased the demand for artificial intelligence (AI)-based edge computing in applications ranging from healthcare monitoring systems to autonomous vehicles. However, the growing complexity of machine learning workloads requires rethinking to make AI amenable to resource constrained environments such as edge devices. To that effect, the entire stack of machine learning, from algorithms to hardware primitives, have been explored to enable energy-efficient intelligence at the edge. </div><div><br></div><div>From the algorithmic aspect, model compression techniques such as quantization are powerful tools to address the growing computational cost of ML workloads. However, quantization, particularly, can result in substantial loss of performance for complex image classification tasks. To address this, a principal component analysis (PCA)-driven methodology to identify the important layers of a binary network, and design mixed-precision networks. The proposed Hybrid-Net achieves a significant improvement in classification accuracy over binary networks such as XNOR-Net for ResNet and VGG architectures on CIFAR-100 and ImageNet datasets, while still achieving up remarkable energy-efficiency. </div><div><br></div><div>Having explored compressed neural networks, there is a need to investigate suitable computing systems to further the energy efficiency. Memristive crossbars have been extensively explored as an alternative to traditional CMOS based systems for deep learning accelerators due to their high on-chip storage density and efficient Matrix Vector Multiplication (MVM) compared to digital CMOS. However, the analog nature of computing poses significant issues due to various non-idealities such as: parasitic resistances, non-linear I-V characteristics of the memristor device etc. To address this, a simplified equation-based modelling of the non-ideal behavior of crossbars is performed and correspondingly, a modified technology aware training algorithm is proposed. Building on the drawbacks of equation-based modeling, a Generalized Approach to Emulating Non-Ideality in Memristive Crossbars using Neural Networks (GENIEx) is proposed where a neural network is trained on HSPICE simulation data to learn the transfer characteristics of the non-ideal crossbar. Next, a functional simulator was developed which includes key architectural facets such as tiling, and bit-slicing to analyze the impact of non-idealities on the classification accuracy of large-scale neural networks.</div><div><br></div><div>To truly realize the benefits of hardware primitives and the algorithms on top of the stack, it is necessary to build efficient devices that mimic the behavior of the fundamental units of a neural network, namely, neurons and synapses. However, efforts have largely been invested in implementations in the electrical domain with potential limitations of switching speed, functional errors due to analog computing, etc. As an alternative, a purely photonic operation of an Integrate-and-Fire Spiking neuron is proposed, based on the phase change dynamics of Ge2Sb2Te5 (GST) embedded on top of a microring resonator, which alleviates the energy constraints of PCMs in electrical domain. Further, the inherent parallelism of wavelength-division multiplexing (WDM) was leveraged to propose a photonic dot-product engine. The proposed computing platform was used to emulate a SNN inferencing engine for image-classification tasks. These explorations at different levels of the stack can enable energy-efficient machine learning for edge intelligence. </div><div><br></div><div>Having explored various domains to design efficient DNN models and studying various hardware primitives based on emerging technologies, we focus on Silicon implementation of compute-in-memory (CIM) primitives for machine learning acceleration based on the more available CMOS technology. CIM primitives enable efficient matrix-vector multiplications (MVM) through parallelized multiply-and-accumulate operations inside the memory array itself. As CIM primitives deploy bit-serial computing, the computations are exposed bit-level sparsity of inputs and weights in a ML model. To that effect, we present an energy-efficient sparsity-aware reconfigurable-precision compute-in-memory (CIM) 8T-SRAM macro for machine learning (ML) applications. Standard 8T-SRAM arrays are re-purposed to enable MAC operations using selective current flow through the read-port transistors. The proposed macro dynamically leverages workload sparsity by reconfiguring the output precision in the peripheral circuitry without degrading application accuracy. Specifically, we propose a new energy-efficient reconfigurable-precision SAR ADC design with the ability to form (n+m)-bit precision using n-bit and m-bit ADCs. Additionally, the transimpedance amplifier (TIA) –required to convert the summed current into voltage before conversion—is reconfigured based on sparsity to improve sense margin at lower output precision. The proposed macro, fabricated in 65 nm technology, provides 35.5-127.2 TOPS/W as the ADC precision varies from 6-bit to 2-bit, respectively. Building on top of the fabricated macro, we next design a hierarchical CIM core micro-architecture that addresses the existing CIM scaling challenges. The proposed CIM core micro-architecture consists of 32 proposed sparsity-aware CIM macros. The 32 macros are divided into 4 matrix-vector multiplication units (MVMUs) consisting of 8 macros each. The core has three unique features: i) it can adaptively reconfigure ADC precision to achieve energy-efficiency and lower latency based on input and weight sparsity, determined by a sparsity controller, ii) it deploys row-gating feature to maintain SNR requirements for accurate DNN computations, and iii) hardware support for load balancing to balance latency mismatches occurring due to different ADC precisions in different compute units. Besides the CIM macros, the core micro-architecture consists of input, weight, and output memories, along with instruction memory and control circuits. The instruction set architecture allows for flexible dataflows and mapping in the proposed core micro-architecture. The sparsity-aware processing core is scheduled to be taped out next month. The proposed CIM demonstrations complemented by our previous analysis on analog CIM systems progressed our understanding of this emerging paradigm in pertinence to ML acceleration.</div>

Utilizing Phase Change Materials (PCM) for Latent Thermal Energy Storage (LTES) applications have previously been extensively researched as a measure to reduce greenhouse gas emissions from energy consumption. In order to make use of the waste heat from industrial processes for LTES purposes, a new demand emerged for PCMs capable of phase change in mid-temperature ranges of 100 °C - 200 °C. This higher temperature requirement made most of the previously studied material inapplicable as they had much lower melting and solidification temperatures. With this in mind, a new generation of PCMs consisting of Sugar Alcohols (SA) has been proposed. Erythritol is seen as an especially promising SA with good thermophysical properties for LTES purposes. However, it has been shown to suffer from severe supercooling, which makes it unreliable in real applications. To eradicate this issue, two additives, Graphene Oxide (GO) and Polyvinylpyrrolidone (PVP) at varying mass fractions were mixed with pure erythritol to form a composite which was studied using the Temperature-history (T-history) method to determine its effectiveness in reducing supercooling. Results show that at its most effective mass fraction, GO reduces supercooling by 28 oC and a 31 oC reduction is seen by the addition of PVP. The impacts on the duration of crystallization was also documented and analyzed using the same method. It was observed that the duration of crystallization was increased with increasing mass fractions of the additives. Other important properties of the composites were also studied in order to determine the overall feasibility for industrial applications. It includes analysis of the storage capacity through latent heat, changes in viscosity along with impacts on thermal diffusivity of the composites. / Att använda fasändringsmaterial (PCM) för termisk energilagring i form av latent värme (LTES) har tidigare extensivt forskats och undersökts som en lösning för att minska utsläppen av växthusgaser från energiförbrukning. För att utnyttja spillvärme från industriella processer för LTES-ändamål uppstod en efterfrågan på PCM som ändrar fas i temperaturer mellan 100 °C - 200 °C. Detta krav på högre temperatur gjorde att de flesta av de tidigare aktuella materialen inte kunde tillämpas eftersom de hade mycket lägre smält- och kristalliseringstemperaturer. Med detta i åtanke har en ny generation av PCM bestående av sockeralkoholer (SA) föreslagits. Erytritol ses som ett särskilt lovande SA med goda egenskaper för LTES-ändamål. Den har dock visat sig drabbas av svår underkylning, vilket gör den opålitligt i verkliga tillämpningar. För att utrota detta problem blandades två tillsatser, Graphene Oxide (GO) och Polyvinylpyrrolidone (PVP) vid olika massfraktioner med ren erytritol för att bilda en komposit som studerades med metoden Temperature-history (T-history) för att bestämma dess effektivitet på att minska underkylningen. Resultaten visar att GO på sin mest effektiva massfraktion minskar underkylningen med 28 oC och tillsats av PVP lyckats minska den med som mest 31 oC. Påverkningarna på varaktighet av kristallisering dokumenterades och analyserades med samma metod. Det var observerad att varaktigheten av kristallisering ökades med ökande massfraktioner av tillsatserna. Även andra viktiga egenskaper hos kompositerna studerades för att avgöra rimligheten att använda dessa för industriella tillämpningar. Det inkluderar analys av lagringskapaciteten genom latent värme, förändringar i viskositet tillsammans med påverkan på kompositernas termiska diffusivitet.

<p dir="ltr">Smart windows, dynamically adjusting optical transmittance, face global adoption challenges due to climatic and economic variability. Aiming these issues, we synthesized a methyl cellulose (MC) salt system with high tunability for intrinsic optical transmittance (89.3%), which can be applied globally to various locations. Specifically, the MC window has superior heat shielding potential below transition temperatures while turning opaque at temperatures above the Lower Critical Solution Temperature (LCST), reducing the solar heat gain by 55%. Such optical tunability is attributable to the particle size change triggered by the temperature-induced reversible coil-to-globular transition. This leads to effective refractive index and scattering modulation, making them prospective solutions for light management systems, an application ahead of intelligent fenestration systems. MC-based windows demonstrated a 9°C temperature decrease compared to double-pane windows on sunny days and a 5°C increase during winters in field tests, while simulations predict an 11% energy savings.</p><p dir="ltr">Incorporating MC-based phase change materials in passive solar panels indicated optimized energy efficiency, offering a sustainable alternative. Real-time simulations validate practical applicability in large-scale solar panels. Furthermore, a temperature-responsive sorbent with a dark layer demonstrates an optimal optical and water uptake performance. Transitioning between radiative cooling and solar heating, the sorbent exhibits high water harvesting efficiency in lab and field tests. With an adjustable LCST at 38 ℃, the cellulose-based sorbent presents a potential solution for atmospheric water harvesting, combining optical switching and temperature responsiveness for sustainable water access. Furthermore, the ubiquitous availability of materials, low cost, and ease-of-manufacturing will provide technological equity and foster our ambition towards net-zero buildings and sustainable future.</p>

The Phase change materials (PCM) have the ability to absorb and release heat as the temperature changes from high to low temperature and vice versa. The use of phase change materials has increased in the construction sector due to the established environmental requirements and the various application benefits, especially in the thermal comfort of building applications and construction of sustainable infrastructure around the world (Berardi and Gallardo, 2019). Over the past decade, many studies have been conducted on the thermal properties of PCM (phase change material), however, few studies have focused on the study effect of PCM on mechanical and physical properties, although of great importance. In this work, three different microencapsulated types of phase change material (PCM) have been studied, while its effect on the mechanical and hydration properties of the cement paste with regard to constant ratio of water to cement ratio has been taken into account. The PCMs that have been studied are the following: Microencapsulated PCM, which is Nextek 24 D, Nextek 57D (Microtek Laboratories) and Croda Therm ME29P (Croda). In this study, various tests were performed on cementitious paste mixed with different doses of PCM to test the effect that PCM has on the cement hydration (under semi-adiabatic and isothermal conditions), the physical properties (setting time, slump flow, density) and the mechanical properties ( compressive strength). The results of this study indicated that both the melting point of the PCM and its amount have a decisive effect on the properties of the cement paste. Finally, the following conclusions have been drawn: • Additions of different dosage levels of the 24D and Croda PCM types showed that an increase in the dosage resulted in impaired mechanical and physical properties such as compressive strength of the cement paste (mechanical) decreased, and the density and random flow decreased (physical). While Nextek 57D did not show a great effect on cement paste according to density and random flow, which gives reduced negative impact on cement paste workability (physical). According to the mechanical properties, Nextek57D PCM with different levels of levels showed immediate positive effect on cement paste compressive strength compared to reference paste (no addition of PCM), and other cement pastes with other PCM types used in this study. • Mikrotek 57D PCM also gives a positive effect at different dose levels compared to two other types of Nextek 24D and Croda PCM regarding the effect of heat flow, which gives rise to hydration heat during the cement hydration process. However, other types of Nextek 24D and Croda in all quantities showed negligible effect on the heat flow during the cement hydration process.

Severe accidents in a Light Water Reactor (LWR) have been a subject of the research for the last three decades. The research in this area aims to further understanding of the inherent physical phenomena and reduce the uncertainties surrounding their quantification, with the ultimate goal of developing models that can be applied to safety analysis of nuclear reactors. The research is also focusing on evaluation of the proposed accident management schemes for mitigating the consequences of such accidents. During a hypothetical severe accident, whatever the scenario, there is likelihood that the core material will be relocated and accumulated in the lower plenum in the form of a debris bed or a melt pool. Physical phenomena involved in a severe accident progression are complex. The interactions of core debris or melt with the reactor structures depend very much on the debris bed or melt pool thermal hydraulics. That is why predictions of heat transfer during melt pool formation in the reactor lower head are important for the safety assessment. The main purpose of the present study is to advance a method for describing turbulent natural convection heat transfer of a melt pool, and to develop a computational platform for cost-effective, sufficiently-accurate numerical simulations and analyses of Core Melt-Structure-Water Interactions in the LWR lower head during a postulated severe core-melting accident. Given the insights gained from Computational Fluid Dynamics (CFD) simulations, a physics-based model and computationally-efficient tools are developed for multi-dimensional simulations of transient thermal-hydraulic phenomena in the lower plenum of a Boiling Water Reactor (BWR) during the late phase of an in-vessel core melt progression. A model is developed for the core debris bed heat up and formation of a melt pool in the lower head of the reactor vessel, and implemented in a commercial CFD code. To describe the natural convection heat transfer inside the volumetrically decay-heated melt pool, we advanced the Effective Convectivity Conductivity Model (ECCM), which was previously developed and implemented in the MVITA code. In the present study, natural convection heat transfer is accounted for by only the Effective Convectivity Model (ECM). The heat transport and interactions are represented through an energy-conservation formulation. The ECM then enables simulations of heat transfer of a high Rayleigh melt pool in 3D large dimension geometry. In order to describe the phase-change heat transfer associated with core debris, a temperature-based enthalpy formulation is employed in the ECM (the phase-change ECM or so called the PECM). The PECM is capable to represent possible convection heat transfer in a mushy zone. The simple approach of the PECM method allows implementing different models of the fluid velocity in a mushy zone for a non-eutectic mixture. The developed models are validated by a dual approach, i.e., against the existing experimental data and the CFD simulation results. The ECM and PECM methods are applied to predict thermal loads to the vessel wall and Control Rod Guide Tubes (CRGTs) during core debris heat up and melting in the BWR lower plenum. Applying the ECM and PECM to simulations of reactor-scale melt pool heat transfer, the results of the ECM and PECM calculations show an apparent effectiveness of the developed methods that enables simulations of long term accident transients. It is also found that during severe accident progression, the cooling by water flowing inside the CRGTs plays a very important role in reducing the thermal load on the reactor vessel wall. The results of the CFD, ECM and PECM simulations suggest a potential of the CRGT cooling as an effective mitigative measure during a severe accident progression. / QC 20101119